Energy Efficiency in Total Nitrogen Removal
at the Kakolanmäki WWTP in Turku
– Using dynamic simulation for optimising process parameters in aeration
Anna Kuokkanen and Ari Niemelä, FCG Finnish Consulting Group Ltd
Different process control parameters and their combinations were scrutinised in fluctuating flow, temperature and loading conditions to optimise
energy consumption and treatment result at the Kakolanmäki waste water treatment plant. The partial by-pass of primary sedimentation used for
ensuring sufficient BOD for denitrification had a significant impact on energy consumption while the effect on treatment result was varying.
Aeration control based on both oxygen concentration and effluent ammonia concentration proved to be robust and well self adjusting.
Background
In an activated sludge plant aeration is crucial for the removal
of organic carbon (BOD) and nitrogen and it is also typically
the biggest consumer of energy. The main objectives for
this work were to find optimal set-point values for aeration
control and suitable ratios for pre-sedimentation by-pass at
the Kakolanmäki waste water treatment plant in view of both
energy efficiency and maximal total nitrogen removal.
concentration in the last aerated zone and the use of aeration
or mixing in the third zone are both controlled based on effluent
ammonia concentration. The influent BOD/N ratio is high due
to industrial wastewaters and pre-sedimentation is partially bypassed to ensure sufficient organic carbon for denitrification
to achieve a high total nitrogen reduction.
The Kakolanmäki WWTP owned by Turun Seudun
Puhdistamo Ltd is a large underground activated sludge
plant with deep aeration basins and sand filtration as tertiary
treatment. It is one of the largest treatment plants in Finland
and it treated 28,5 Mm3 of municipal wastewater in 2010.
The treatment plant is new and well instrumented and the
level of automation is high. The set-point value for oxygen
TURUN SEUDUN PUHDISTAMO OY
KAKOLANMÄEN JÄTEVEDENPUHDISTAMO, IV/IV 2010
TULOKUORMA *
BOD7
SS
tot-N
tot-P
28 000
33 000
4 300
670
QKA
73 000
QMAX
142 000
6 000
qMIT
12 000
qMAX
qMAX(BIOL.) 8 700
6
Alkalit.
ESISELKEYTYS
HIEKANEROTUS
VKOK.
1500 m³
VYKS.
375 m³
t, qKA
30 min
t, qMAX
8 min
kg/d
kg/d
kg/d
kg/d
m³/d
m³/d
m³/h
m³/h
m³/h *
mmol/l
KARKEAVÄLPPÄYS
AKOK.
AYKS.
Sh(qKA)
Sh (qMAX)
2 920
730
1.0
2.4
BHK-red.
N-red.
P-red.
SS-red.
* 4 linjaa
55
20
65
65
HIENOVÄLPPÄYS
ILMASTUS
TULEVA JÄTEVESI
m²
m²
m/h *
m/h *
%
%
%
%
BOD/N
BOD/P
6.5
42
VKOK.
VALLAS
h
θc
ILMASTUKSEEN
0.32
Lv
3.9
MLSS
0.08
LMLSS
AOR
35 400
AIRMAX 17 400
5.0
46
BOD/N
BOD/P
41 %
ohitus, ka
60 000
15 000
15.0
12.4
JÄLKISELKEYTYS
8 400
2 100
0.36
1.04
m³
m³
m
d
AKOK.
AALLAS
Sh(qKA)
Sh(qMAX)
kg/m³/d
kg/m³
kg/kg/d
kgO2/d
n-m³/h
SMLSS(qKA)
SMLSS(QMAX BIO
Lisähiili
Nitraattikierto
210 000
JÄLKISELKEYTETTY
m²
m²
m/h
m/h
BOD7
SS
tot N
3.1 kgSS/m²/h
7.3 kgSS/m²/h
KAASUNPOISTO
1400 m³
VKOK.
VALLAS
350 m³
m³/d
Polymeeri
5.7 mg/l
9.7 mg/l
10.2 mg/l
1.6 mg/l
0.3 mg/l
1.9 mmol/l
NH4-N
tot P
Alkalit.
Ferrosulfaatti
1000 kg/d
60 kg/d
Hiekka
Kalkki
0 kg/d
Ferrosulfaatti
7600 kg/d
HIEKKASUODATUS
AKOK.
1 000 m²
AYKS.
50 m²
Sh (qKA)
3.0 m/h
Sh (qMAX, biol.)
9 m/h
Sh (qMAX, biol.+
m/h
SSh (qMAX, biol.)
120
YLIJÄÄMÄLIETE
3.9 kgMLSS/m³
18 900 kgMLSS/d
4 800 m³/d
RAAKASEKALIETE
32 500 kgTS/d
3.7 %TS
880 m³/d
LIETTEEN KUIVAUS
q
50 m³/h
TS 2 000 kg/h
3.7 %TS
gSS/m2 h
RAAKASEKALIETTEEN
VÄLIVARASTO
200 m³
V
5.5 h
t
87 000 m³/d
palautusliete
OHITUSVESIEN KÄSITTELY
KUIVATTU LIETE
31 900 kgTS/d
18 %TS
180 m³/d (7d)
16 300 m³/jakso
Ferrisulfaatti
PUHDISTUSTULOS
HUUHTELUVESIALTAAT BOD7
V 2 x 150 m³
SS
tot N
NH4-N
tot P
2.4
2.7
9.8
1.2
0.1
mg/l
mg/l
mg/l
mg/l
mg/l
Figure 1.
Process mass balance
chart of Kakolanmäki
WWTP.
SIILOVARASTOINTI
Polymeeri
3.6 kg/tTS
V
116 kg/d
t
TURUN SEUDUN PUHDISTAMO OY
2x160 m³
KAKOLANMÄEN JÄTEVEDENPUHDISTAMO
1.8 d
Osmontie 34, PL 30, 00601 HKI
jatkokäsittelyyn
* toteutunut virtaama ilmastukseen
puh.
010 409 5000
fax.
010 409 5007
AINETASE IV/IV 2010
21.1.2011
Niemelä / Kuokkanen / Klemetti
Methods
After calibrating the model, nitrogen removal results and air
consumption were calculated during two different simulated
four week periods using different process control strategies.
A statistical analysis of treatment results during 1.1.2010–
30.6.2011 was also made comparing total nitrogen removal
with e.g. nitrification result, pre-sedimentation by-pass ratio
and the BOD/N-ratio in aeration.
240.0
240.0
240.0
240.0
A dynamic model of pre-sedimentation and the activated
sludge process was made using the commercial software
Ilmastusilma
GPS-X and the Activated
sludge model (ASM).
192.0
air consumption
95
NO3-N + NH4-N
144.0
280 000
260 000
7,5
240 000
7
m3/d
96.0
mg/l
8
Total nitrogen reduction, %
300 000
8,5
48.0
[39] air flow at field conditions [m3/d] *10^ 3
192.0
144.0
96.0
48.0
0.0
[42(1)] air flow at field conditions [m3/d] *10^ 3
100
320 000
9
90
85
80
75
70
220 000
65
0.0
192.0
144.0
96.0
48.0
0.0
[42(2)] air flow at field conditions [m3/d] *10^ 3
192.0
144.0
96.0
48.0
0.0
[46] air flow at field conditions [m3/d] *10^ 3
C:\Data\nwc2011\lähtöaineisto\Kakolanmäki_käyttötuki_prosmit_IV_2010.xls
0.0
1.2
2.4
3.6
4.8
6.0
6,5
200 000
1
2A
2B
3A
3B
4A
4B
5A
5B
5C
5D
6A
6B
6C
7A
7B
7C
60
0
5
Time [days]
10
15
20
25
30
35
40
45
50
By-pass ratio of presedimentation, %
Figure 2. Air consumption during a six day period,
simulated (solid line) and measured (+).
Figure 3. Air consumption (m3/d) and effluent nitrogen
(mg/l) with different process control strategies.
Figure 4. Nitrogen reductions at different ratios of
pre-sedimentation by-pass.
Results and Conclusions
With a sufficiently high BOD/N ratio of
the influent the total nitrogen removal
was mainly dependent of nitrification and
internal recycle. Mainly all recycled nitrate
was consumed during the anoxic phase.
Energy_efficiency_in_total_nitrogen___in_Kakola.indd 2
The role of pre-sedimentation by-pass for
ensuring high nitrogen reduction was smaller
than estimated in process design, due to a
higher BOD content of the influent. Its impact
on energy consumption was considerable.
Thus smaller by-pass ratios for winter and
summer were recommended.
Using on-line measurement of effluent
ammonia concentration and automation
control for choosing between aeration or
mixing in zone 3 and adjusting the set-point
values for oxygen concentration in zone 6
proved to be effective and un-sensitive for
moderate changes of the user defined set
point values.
The set-point values for oxygen levels in
aeration zones 4 and 5 had a significant
effect on air consumption while only little
effect on the treatment result for values
above 1 mg of oxygen per litre, indicating
that using ammonia-based set-point values
for aeration control of all basins could save
more energy.
9.11.2011 17:16:32